iriss_manual_ratings_long <- iriss_manual_ratings %>%
rename(rater_id = ResponseId) %>%
pivot_longer(cols = frisbee.0.condition:bubblewrap.4.use,
names_to = "stimulus_metadata",
values_to = "value") %>%
mutate(metadata = str_extract(stimulus_metadata, "[^.]+$"),
stimulus_metadata = str_remove(stimulus_metadata, "\\.[^.]+$")) %>%
separate_wider_delim(stimulus_metadata,
".",
names = c("object", "trial_num")) %>%
pivot_wider(
names_from = "metadata",
values_from = "value") %>%
rename(submitter_id = ResponseId)
# Pivot to give each creativity rating its own column
iriss_manual_ratings_metrics <- iriss_manual_ratings_long %>%
pivot_longer(cols = c_frisbee_1:u_bubble_5,
names_to = "trial",
values_to = "rating") %>%
mutate(rating = as.numeric(rating)) %>%
mutate(metric = str_extract(trial, "^[A-Za-z]+(?=_)")) %>%
mutate(metric = case_when(metric == "c" ~ "creativity",
metric == "o" ~ "originality",
metric == "u" ~ "usefulness")) %>%
dplyr::select(rater_id, object, trial_num, submitter_id, condition, use, trial, metric, rating) %>%
mutate(trial = str_remove(trial, "^._")) %>%
mutate(trial_num = as.numeric(trial_num),
trial_num = trial_num+1) %>%
unite(col="stimulus", c("object", "trial_num")) %>%
mutate(trial = str_replace_all(trial, "bubble", "bubblewrap")) %>% # Check names!
filter(stimulus==trial) %>%
pivot_wider(names_from = "metric",
values_from = "rating") %>%
mutate(object = str_extract(stimulus, "^[A-Za-z]+")) %>%
relocate(object, .after = "stimulus") %>%
mutate(use_word_count = str_count(use, "\\S+")) %>%
relocate(use_word_count, .after = use) %>%
mutate(condition=case_when(condition=="Pilot"~"High-Agency",
condition=="Passenger"~"Low-Agency",
condition=="Control"~"Control"))
# Select process variables from full dataset
process_vars <- iriss_trial_data %>%
dplyr::select(submitter_id, object, starts_with("conv_with_ai"), starts_with("consideration_aid"), starts_with("intrinsic_motivation")) %>%
distinct()
write_csv(iriss_manual_ratings_metrics, "data/iriss_manual_ratings_metrics.csv")